Equity of utilisation of cardiovascular care and mental health services in England: a cohort-based cross-sectional study using small-area estimation

Abstract

BackgroundA strong policy emphasis on the need to reduce both health inequalities and unmet need in deprived areas has resulted in the substantial redistribution of English NHS funding towards deprived areas. This raises the question of whether or not socioeconomically disadvantaged people continue to be disadvantaged in their access to and utilisation of health care.ObjectivesTo generate estimates of the prevalence of cardiovascular disease (CVD) and common mental health disorders (CMHDs) at a variety of scales, and to make these available for public use via Public Health England (PHE). To compare these estimates with utilisation of NHS services in England to establish whether inequalities of use relative to need at various stages on the health-care pathway are associated with particular sociodemographic or other factors.DesignCross-sectional analysis of practice-, primary care trust- and Clinical Commissioning Group-level variations in diagnosis, prescribing and specialist management of CVD and CMHDs relative to the estimated prevalence of those conditions (calculated using small-area estimation).ResultsThe utilisation of CVD care appears more equitable than the utilisation of care for CMHDs. In contrast to the reviewed literature, we found little evidence of underutilisation of services by older populations. Indeed, younger populations appear to be less likely to access care for some CVD conditions. Nor did deprivation emerge as a consistent predictor of lower use relative to need for either CVD or CMHDs. Ethnicity is a consistent predictor of variations in use relative to need. Rates of primary management are lower than expected in areas with higher percentages of black populations for diabetes, stroke and CMHDs. Areas with higher Asian populations have higher-than-expected rates of diabetes presentation and prescribing and lower-than-expected rates of secondary care for diabetes. For both sets of conditions, there are pronounced geographical variations in use relative to need. For instance, the North East has relatively high levels of use of cardiac care services and rural (shire) areas have low levels of use relative to need. For CMHDs, there appears to be a pronounced ‘London effect’, with the number of people registered by general practitioners as having depression, or being prescribed antidepressants, being much lower in London than expected. A total of 24 CVD and 41 CMHD prevalence estimates have been provided to PHE and will be publicly available at a range of scales, from lower- and middle-layer super output areas through to Clinical Commissioning Groups and local authorities.ConclusionsWe found little evidence of socioeconomic inequality in use for CVD and CMHDs relative to underlying need, which suggests that the strong targeting of NHS resources to deprived areas may well have addressed longstanding concerns about unmet need. However, ethnicity has emerged as a significant predictor of inequality, and there are large and unexplained geographical variations in use relative to need for both conditions which undermine the principle of equal access to health care for equal needs. The persistence of ethnic variations and the role of systematic factors (such as rurality) in shaping patterns of utilisation deserve further investigation, as does the fact that the models were far better at explaining variation in use of CVD than mental health services.FundingThe National Institute for Health Research Health Services and Delivery Research programme.

Investigating geographical variation in the use of mental health services by area of England: a cross-sectional ecological study

“…Area deprivation may impact the number of people in contact with mental health services through affecting both the prevalence of mental disorders and health service utilization. Higher deprivation can result in higher use of formal services through increased comorbidity [ 32 ] [ 33 ], reduced social support [ 34 ] or reduced availability of non-healthcare resources to draw from [ 22 ]. There is evidence from literature that areas with higher deprivation have a higher number of compulsory admissions to mental health hospitals [ 35 ], for example, one additional percentage point in population income deprivation (according to the European Deprivation Index definition) has previously been shown to be associated with a 1.6% increase in admissions to hospital with severe mental illness [ 11 ].…”

“…The fact that areas with a higher proportion of the population who are BAME had lower service use, after the prevalence of mental disorders is taken into account, suggests that there may be differences in access to services related to ethnicity. It has been previously found that people of black African or Caribbean backgrounds are overrepresented in inpatient mental health services but underrepresented in community services [ 22 ], and that Black patients may need to navigate more complex care pathways before being accepted by secondary mental health services [ 39 ]. In contrast those from Asian backgrounds have been previously found to use inpatient units less than White patients [ 39 ].…”

“…In this study, there was suggestive evidence that areas with higher population density had lower numbers of people in contact with mental health services per 100,000 population once the prevalence of mental disorders was controlled for, although this was not statistically significant at the 5% level. Population density may reflect geographical proximity to services, but not necessarily population coverage, as found by Asthana and colleagues, who observed that the densely populated area of London has lower than expected uptake of services for common mental disorders [ 22 ]. There also may be service limits that constrain geographical variation in the number of people in contact with services relative to need, as in areas where demand is very high, services may not be able to expand sufficiently to meet need and so put in place higher thresholds for accepting patients.…”

“…Area level factors identified that may influence the proportion of people with a mental disorder who receive treatment include population density [ 18 ], urban-rural location [ 19 ] and ethnicity [ 20 ] [ 21 ]. A study that compared estimated prevalence rates of mental disorder with observed treatment rates in primary care in small areas of England found that ethnicity was a consistent predictor of geographical variations in service use relative to need [ 22 ], with areas with higher proportion of black populations having significantly lower numbers of people in treatment for depression than the expected prevalence, suggesting reduced help seeking behaviour or poorer access to services for this group. The authors also observed a pronounced ‘London effect’, where the number of people being treated by primary care for depression in London was found to be much lower than expected on the basis of modelled estimates [ 22 ].…”

How data science can advance mental health research

“…Novel data linkageslinking health to survey data with better socioeconomic measures or even to robustly anonymised Census outputis one way forward. [46][47][48] There might also be scope to identify educational and occupational status from electronic health and other records. 49 However, this approach is currently accompanied by substantial practical and ethical challenges.…”